CN114625741A - Data processing method and system based on artificial intelligence and cloud platform - Google Patents
Data processing method and system based on artificial intelligence and cloud platform Download PDFInfo
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Abstract
According to the data processing method, the data processing system and the cloud platform based on the artificial intelligence, the first interactive report recognition strategy information covering the target interactive industrial report information result is processed through the preset report characteristic description thread to obtain the target result description content corresponding to the target interactive industrial report information result, the result interaction strategy after the target result description content is corrected is used for carrying out result processing on the second interactive report recognition strategy information transmitted by a user, and the report exchange information set of the simulation training is constructed according to the third interactive report recognition strategy information covering the target interactive industrial report information result. The method can process the interactive industrial report information result in the process of simulating and training the report into one interactive industrial report information result to interact with the user while the filling content of the report is not changed aiming at one user, so that the effect of interactive template statistics in the report process is improved, the integrity of the report is built to a greater extent, and the data processing efficiency is improved.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a data processing method and system based on artificial intelligence and a cloud platform.
Background
In the continuous progress of artificial intelligence technology, artificial intelligence can be accurate gather every information, then classify the information, can be accurate like this handle every report information, can not only improve the efficiency of report information processing like this, can also effectual reduce cost.
The report template is constructed through artificial intelligence, so that corresponding information input can be rapidly and accurately carried out, the input efficiency can be improved, and the input accuracy can be improved. However, the current report template is imperfect in construction and integrity, resulting in poor data processing effect.
Disclosure of Invention
In view of this, the present application provides a data processing method, system and cloud platform based on artificial intelligence.
In a first aspect, a data processing method based on artificial intelligence is provided, the method including:
analyzing the received interactive industrial report information, and performing identification processing to obtain a target interactive industrial report information result;
acquiring first interactive report identification strategy information covering the target interactive industrial report information result, and transmitting the first interactive report identification strategy information to a preset configured report characteristic description thread to obtain target result description content corresponding to the target interactive industrial report information result;
modifying the result description content of the result interaction strategy stored in advance into the target result description content, and performing result processing on second interaction report identification strategy information transmitted by a user according to the modified result interaction strategy to obtain third interaction report identification strategy information covering the target interaction industrial report information result;
and constructing a report exchange information set for simulation training according to the third interactive report recognition strategy information.
Further, the step of transmitting the first interactive report identification policy information to a preset configured report feature description thread to obtain a target result description content corresponding to the target interactive industrial report information result includes:
selecting a historical result description vector set corresponding to the first interactive report identification strategy information;
and transmitting the historical result description vector set to the report characteristic description thread to obtain target result description content corresponding to the target interactive industrial report information result.
Further, the step of performing result processing on the second interactive report identification policy information transmitted by the user according to the modified result interaction policy to obtain third interactive report identification policy information covering the target interactive industrial report information result includes:
selecting report key attribute contents of the second interactive report identification strategy information, wherein the report key attribute contents comprise report standard attribute contents;
processing the report standard attribute content through the modified result interaction strategy to obtain a result verification identification tag set covering the target interaction industrial report information result;
and performing result feedback training on the report standard attribute content and the result verification identification label set to obtain third interactive report identification strategy information covering the target interactive industrial report information result.
Further, the report feature description thread is obtained based on a convolutional neural training network configuration by using basic information of a first interactive report identification strategy of at least one interactive industrial report information result and basic information of a second interactive report identification strategy of one of the users, wherein the at least one interactive industrial report information result comprises the target interactive industrial report information result.
Further, before obtaining a target interactive industrial reporting information result in the identification process from the received interactive industrial reporting information, the method further comprises:
the report feature description thread configured according to the configuration basic information, which is set in advance, specifically includes: obtaining configuration basic information, wherein the configuration basic information comprises basic information of a first interactive report identification strategy of at least one interactive industrial report information result and basic information of a second interactive report identification strategy of one user, and the at least one interactive industrial report information result comprises a target interactive industrial report information result;
selecting a corresponding report description basic information set from the basic information of the second interactive report identification strategy of one of the users;
aiming at each interactive industrial report information result, selecting a corresponding result description basic information set from basic information of a first interactive report identification strategy of the interactive industrial report information result;
and configuring a basic unit training thread according to the report description basic information set and a result description basic information set corresponding to each interactive industrial report information result to obtain the report characteristic description thread, and storing the report characteristic description thread in a data processing terminal.
Further, the step of configuring the basic unit training thread according to the report description basic information set and the result description basic information set corresponding to each interactive industrial report information result includes:
transmitting a result description basic information set corresponding to each interactive industrial report information result to the basic unit training thread to obtain a result description content of each interactive industrial report information result;
correcting the result description content of a preset result interaction strategy according to the result description content of each interactive industrial report information result, and transmitting the report description basic information set to the corrected result interaction strategy to obtain a corresponding interactive result description basic information set;
and correcting the result description content of the basic unit training thread according to the result description basic information set of each interactive industrial report information result and the corresponding basic information set described by the interactive result to obtain the report characteristic description thread.
Further, the step of correcting the result description content of the basic unit training thread according to the result description basic information set of each interactive industrial report information result and the corresponding basic information set of the interactive result description comprises the following steps:
calculating a model evaluation information characteristic vector between a result description basic information set of each interactive industrial report information result and a corresponding interactive result description basic information set;
and after updating the result description content of the basic unit training thread according to the model evaluation information feature vector, performing iterative configuration, and outputting a report form feature description thread obtained by configuration until the basic unit training thread meets the configuration ending condition.
Further, the configuration end condition includes at least one of the following conditions:
the model evaluation information characteristic vector is not weakened in error any more;
the model evaluation information characteristic vector is lower than a set standard attenuation period;
the iterative configuration frequency reaches the set frequency.
In a second aspect, there is provided an artificial intelligence based data processing system comprising a processor and a memory in communication with each other, the processor being configured to read a computer program from the memory and execute the computer program to implement the above method.
In a third aspect, a cloud platform, comprising:
a memory for storing a computer program;
a processor coupled to the memory for executing the computer program stored by the memory to implement the above-described method.
According to the data processing method, the data processing system and the cloud platform based on the artificial intelligence, the first interactive report recognition strategy information covering the target interactive industrial report information result is processed through the preset report characteristic description thread to obtain the target result description content corresponding to the target interactive industrial report information result, the result interaction strategy after the target result description content is corrected is used for carrying out result processing on the second interactive report recognition strategy information transmitted by a user, and the report exchange information set of the simulation training is constructed according to the third interactive report recognition strategy information covering the target interactive industrial report information result. Therefore, the interactive industrial report information result in the report simulation training process can be processed into one interactive industrial report information result for interacting with the user while the report filling content is not changed for one user, the interactive template counting effect in the report process is improved, the integrity of the report is built to a greater extent, and the data processing efficiency is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a flowchart of a data processing method based on artificial intelligence according to an embodiment of the present disclosure.
Fig. 2 is a block diagram of an artificial intelligence based data processing apparatus according to an embodiment of the present disclosure.
FIG. 3 is an architecture diagram of an artificial intelligence based data processing system according to an embodiment of the present application.
Detailed Description
In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
Referring to fig. 1, a data processing method based on artificial intelligence is shown, which may include the technical solutions described in the following steps 100-400.
And step 100, analyzing the received interactive industrial report information, and identifying to obtain a target interactive industrial report information result.
200, acquiring first interactive report identification strategy information covering the target interactive industrial report information result, and transmitting the first interactive report identification strategy information to a preset configured report characteristic description thread to obtain target result description content corresponding to the target interactive industrial report information result.
And 400, constructing a report exchange information set for simulation training according to the third interactive report recognition strategy information.
It can be understood that, when the technical solutions described in the above steps 100 to 400 are executed, the first interactive report identification policy information covering the target interactive industrial report information result is processed through the preset configured report characteristic description thread to obtain the target result description content corresponding to the target interactive industrial report information result, the result interaction policy modified into the target result description content is used to perform result processing on the second interactive report identification policy information transmitted by the user, and the report exchange information set of the simulation training is constructed according to the third interactive report identification policy information covering the target interactive industrial report information result. Therefore, the interactive industrial report information result in the report simulation training process can be processed into one interactive industrial report information result for interacting with the user while the filling content of the report is not changed, the interactive template counting effect in the report process is further improved, and the integrity of the report is built to a greater extent.
In an alternative embodiment, the inventor finds that, when the first interactive report identification policy information is transmitted to a report feature description thread configured in advance, there is a problem that the set of historical result description vectors is inaccurate, so that it is difficult to accurately obtain the target result description content corresponding to the target interactive industrial report information result, and in order to improve the above technical problem, the step of transmitting the first interactive report identification policy information described in step 200 to a report feature description thread configured in advance to obtain the target result description content corresponding to the target interactive industrial report information result may specifically include the technical solutions described in the following steps q1 and q 2.
And q1, selecting a historical result description vector set corresponding to the identification strategy information of the first interactive report.
And q2, transmitting the historical result description vector set to the report feature description thread to obtain target result description content corresponding to the target interactive industrial report information result.
It can be understood that when the technical solutions described in the above step q1 and step q2 are executed, and the first interactive report identification policy information is transmitted to the report feature description thread configured in advance, the problem that the set of historical result description vectors is inaccurate is solved, so that the target result description content corresponding to the target interactive industrial report information result can be accurately obtained.
In an alternative embodiment, the inventor finds that, when performing result processing on the second interactive report identification policy information transmitted by the user according to the modified result interaction policy, there is a problem that the content of the key attribute of the report is inaccurate, so that it is difficult to accurately obtain the third interactive report identification policy information covering the target interactive industrial report information result, and in order to improve the above technical problem, the step of performing result processing on the second interactive report identification policy information transmitted by the user according to the modified result interaction policy, to obtain the third interactive report identification policy information covering the target interactive industrial report information result, which is described in step 300, may specifically include the technical solutions described in the following step w 1-step w 3.
And step w1, selecting report key attribute contents of the second interactive report identification strategy information, wherein the report key attribute contents comprise report standard attribute contents.
And step w2, processing the report standard attribute content through the modified result interaction strategy to obtain a result verification identification tag set covering the target interaction industrial report information result.
And w3, performing result feedback training on the report standard attribute content and the result verification identification label set to obtain third interactive report identification strategy information covering the target interactive industrial report information result.
It can be understood that when the technical solution described in the above step w 1-step w3 is executed, and the result processing is performed on the second interactive report recognition strategy information transmitted by the user according to the modified result interaction strategy, the problem that the content of the report key attribute is inaccurate is solved, so that the third interactive report recognition strategy information covering the target interactive industrial report information result can be accurately obtained.
In an alternative embodiment, the report charactering thread is obtained based on a convolutional neural training network configuration using basic information of a first interactive report identification policy of at least one interactive industrial report information result and basic information of a second interactive report identification policy of one of the users, wherein the at least one interactive industrial report information result includes the target interactive industrial report information result. The configuration can be accurately performed.
Based on the above basis, before the target interactive industrial reporting information result is obtained in the identification process of the received interactive industrial reporting information, the following technical solutions described in steps e1 to e4 may be further included.
Step e1, configuring and obtaining the report feature description thread according to the configuration basic information, which is set in advance, and specifically includes: obtaining configuration basic information, wherein the configuration basic information comprises basic information of a first interactive report identification strategy of at least one interactive industrial report information result and basic information of a second interactive report identification strategy of one user, and the at least one interactive industrial report information result comprises a target interactive industrial report information result.
And e2, selecting the corresponding report description basic information set from the basic information of the second interactive report identification strategy of one of the users.
And e3, aiming at each interactive industrial report information result, selecting a corresponding result description basic information set from the basic information of the first interactive report identification strategy of the interactive industrial report information result.
And e4, configuring the basic unit training thread according to the report description basic information set and the result description basic information set corresponding to each interactive industrial report information result to obtain the report characteristic description thread, and storing the report characteristic description thread in the data processing terminal.
It can be understood that when the technical solutions described in the above steps e 1-e 4 are executed, the accuracy of the report feature description thread can be improved through configuration.
In an alternative embodiment, the inventor finds that, when configuring the basic unit training thread according to the report description basic information set and the result description basic information set corresponding to each interactive industrial report information result, there is a problem that the content of the result description is not accurate, so that it is difficult to configure accurately, and in order to improve the above technical problem, the step of configuring the basic unit training thread according to the report description basic information set and the result description basic information set corresponding to each interactive industrial report information result described in step e4 may specifically include the technical solutions described in the following step e 41-step e 43.
And e41, transmitting the result description basic information set corresponding to each interactive industrial report information result to the basic unit training thread to obtain the result description content of each interactive industrial report information result.
And e42, correcting the result description content of the preset result interaction strategy according to the result description content of each interactive industrial report information result, and transmitting the report description basic information set to the corrected result interaction strategy to obtain a corresponding interaction result description basic information set.
And e43, correcting the result description content of the basic unit training thread according to the result description basic information set of each interactive industrial report information result and the corresponding interactive result description basic information set, and obtaining the report characteristic description thread.
It can be understood that, when the technical solutions described in the above steps e 41-e 43 are executed, and the basic unit training thread is configured according to the report description basic information set and the result description basic information set corresponding to each interactive industrial report information result, the problem of inaccurate result description content is improved, so that the configuration can be accurately performed.
In an alternative embodiment, the inventors found that, when the result description content of the basic unit training thread is corrected according to the result description basic information set of each interactive industrial report information result and the corresponding basic information set of the interactive result description, there is a problem that the model evaluation information feature vector is inaccurate, so that it is difficult to accurately correct the result description content of the basic unit training thread.
And r1, calculating model evaluation information characteristic vectors between the result description basic information set of each interactive industrial report information result and the corresponding interactive result description basic information set.
And r2, updating the result description content of the basic unit training thread according to the model evaluation information feature vector, then performing iterative configuration, and outputting a report feature description thread obtained by configuration until the basic unit training thread meets the configuration ending condition.
It can be understood that, when the technical solutions described in the above steps r1 and r2 are executed, when the result description content of the basic unit training thread is corrected according to the result description basic information set of each interactive industrial report information result and the corresponding basic information set of the interactive result description, the problem that the model evaluation information feature vector is inaccurate is improved, so that the correction can be accurately performed.
In an alternative embodiment, the configuration ending condition includes at least one of the following conditions, and specifically may include the technical solutions described in the following steps a1 to a 3.
Step a1, the model evaluates the information feature vector to no longer be error-attenuated.
And a step a2, the model evaluation information characteristic vector is lower than a set standard attenuation period.
Step a3, the configuration frequency is iterated to reach the set frequency.
It can be understood that when the technical solutions described in the above steps a 1-a 3 are executed, the accuracy of configuring the ending condition can be improved through multi-dimensional analysis.
In a possible embodiment, the inventor finds that, when constructing the report exchange information set of the simulation training according to the third interactive report recognition strategy information, there is a problem that a plurality of report attribute segments are inaccurate, so that it is difficult to accurately construct the report exchange information set of the simulation training, and in order to improve the above technical problem, the step of constructing the report exchange information set of the simulation training according to the third interactive report recognition strategy information described in step 400 may specifically include the technical solutions described in the following steps s 1-s 4.
And step s1, dividing the third interactive report identification strategy information into a plurality of report attribute segments according to a set interval period.
Step s2, for each report attribute segment, identifying a report content description vector of the report attribute segment, where the report content description vector includes a report description, a word meaning description and a report element description, the word meaning description is used for controlling the word meaning state of the simulated training, and the report element description is used for controlling the simulated training state of the simulated training.
And step s3, generating the business session segment of the simulation training corresponding to the report attribute segment according to the report description, the word meaning description and the report element description.
And step s4, integrating each report attribute segment and the corresponding business session segment thereof to obtain the report exchange information set of the simulated training, and displaying the report exchange information set of the simulated training.
It can be understood that, when the technical solution described in the above step s 1-step s4 is executed, and when the report exchange information set of the simulated training is constructed according to the third interactive report recognition strategy information, the problem that the plurality of report attribute segments are inaccurate is solved, so that the report exchange information set of the simulated training can be accurately constructed.
On the basis, please refer to fig. 2 in combination, the present embodiment provides an artificial intelligence based data processing apparatus 200, applied to a data processing terminal, the apparatus comprising:
the result identification module 210 is configured to analyze the received interactive industrial report information and perform identification processing to obtain a target interactive industrial report information result;
a content obtaining module 220, configured to obtain first interactive report identification policy information covering the target interactive industrial report information result, and transmit the first interactive report identification policy information to a preset configured report feature description thread to obtain target result description content corresponding to the target interactive industrial report information result;
an information obtaining module 230, configured to modify result description content of a result interaction policy stored in advance into the target result description content, and perform result processing on second interaction report identification policy information transmitted by a user according to the modified result interaction policy to obtain third interaction report identification policy information covering the target interaction industrial report information result;
and the information building module 240 is configured to build a report exchange information set of the simulation training according to the third interactive report recognition strategy information.
On the basis of the above, please refer to fig. 3, this embodiment shows an artificial intelligence based data processing system 300, which includes a processor 310 and a memory 320, which are communicated with each other, and the processor 310 is configured to read a computer program from the memory 320 and execute the computer program, so as to implement the above-mentioned method.
On the basis, the embodiment further provides a cloud platform, including: a memory for storing a computer program; a processor coupled to the memory for executing the computer program stored by the memory to implement the above-described method.
In summary, based on the above-mentioned scheme, the first interactive report identification policy information covering the target interactive industrial report information result is processed through the preset configured report characteristic description thread to obtain the target result description content corresponding to the target interactive industrial report information result, the result interaction policy modified into the target result description content is used to perform result processing on the second interactive report identification policy information transmitted by the user, and the report exchange information set of the simulation training is constructed according to the third interactive report identification policy information covering the target interactive industrial report information result. Therefore, the interactive industrial report information result in the report simulation training process can be processed into one interactive industrial report information result for interacting with the user while the filling content of the report is not changed, the interactive template counting effect in the report process is further improved, and the integrity of the report is built to a greater extent.
It should be appreciated that the system and its modules shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).
It is to be noted that different embodiments may produce different advantages, and in different embodiments, the advantages that may be produced may be any one or combination of the above, or any other advantages that may be obtained.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.
Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.
Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereof. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.
The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, and the like, or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.
Computer program code required for the operation of various portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).
Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.
Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the numbers allow for adaptive variation. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit-preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.
The entire contents of each patent, patent application publication, and other material cited in this application, such as articles, books, specifications, publications, documents, and the like, are hereby incorporated by reference into this application. Except where the application is filed in a manner inconsistent or contrary to the present disclosure, and except where the claim is filed in its broadest scope (whether present or later appended to the application) as well. It is noted that the descriptions, definitions and/or use of terms in this application shall control if they are inconsistent or contrary to the statements and/or uses of the present application in the material attached to this application.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application can be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those embodiments explicitly described and depicted herein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of artificial intelligence based data processing, the method comprising:
analyzing the received interactive industrial report information, and performing identification processing to obtain a target interactive industrial report information result;
acquiring first interactive report identification strategy information covering the target interactive industrial report information result, and transmitting the first interactive report identification strategy information to a preset configured report characteristic description thread to obtain target result description content corresponding to the target interactive industrial report information result;
modifying the result description content of the result interaction strategy stored in advance into the target result description content, and performing result processing on second interaction report identification strategy information transmitted by a user according to the modified result interaction strategy to obtain third interaction report identification strategy information covering the target interaction industrial report information result;
and constructing a report exchange information set for simulation training according to the third interactive report recognition strategy information.
2. The artificial intelligence based data processing method according to claim 1, wherein the step of transmitting the first interactive report identification policy information to a preset configured report feature description thread to obtain a target result description content corresponding to the target interactive industrial report information result comprises:
selecting a historical result description vector set corresponding to the first interactive report identification strategy information;
and transmitting the historical result description vector set to the report characteristic description thread to obtain target result description content corresponding to the target interactive industrial report information result.
3. The artificial intelligence based data processing method according to claim 3, wherein the step of performing result processing on the second interactive report identification policy information transmitted by the user according to the modified result interaction policy to obtain third interactive report identification policy information covering the target interactive industrial report information result comprises:
selecting report key attribute contents of the second interactive report identification strategy information, wherein the report key attribute contents comprise report standard attribute contents;
processing the report standard attribute content through the modified result interaction strategy to obtain a result verification identification tag set covering the target interaction industrial report information result;
and performing result feedback training on the report standard attribute content and the result verification identification label set to obtain third interactive report identification strategy information covering the target interactive industrial report information result.
4. The artificial intelligence based data processing method of one of claims 1-3, wherein the report characterization thread is obtained based on a convolutional neural training network configuration using basic information of a first interactive report identification policy of at least one interactive industrial report information result and basic information of a second interactive report identification policy of one of the users, wherein the at least one interactive industrial report information result comprises the target interactive industrial report information result.
5. The artificial intelligence based data processing method of one of claims 1-3, wherein prior to obtaining a target interactive industrial reporting information result from the received interactive industrial reporting information in the recognition process, the method further comprises:
the report feature description thread configured according to the configuration basic information, which is set in advance, specifically includes: acquiring configuration basic information, wherein the configuration basic information comprises basic information of a first interactive report identification strategy of at least one interactive industrial report information result and basic information of a second interactive report identification strategy of one user, and the at least one interactive industrial report information result comprises a target interactive industrial report information result;
selecting a corresponding report description basic information set from the basic information of the second interactive report identification strategy of one of the users;
aiming at each interactive industrial report information result, selecting a corresponding result description basic information set from basic information of a first interactive report identification strategy of the interactive industrial report information result;
and configuring a basic unit training thread according to the report description basic information set and a result description basic information set corresponding to each interactive industrial report information result to obtain the report characteristic description thread, and storing the report characteristic description thread in a data processing terminal.
6. The artificial intelligence based data processing method according to claim 5, wherein the step of configuring the basic unit training thread according to the report description basic information set and the result description basic information set corresponding to each interactive industrial report information result comprises:
transmitting a result description basic information set corresponding to each interactive industrial report information result to the basic unit training thread to obtain a result description content of each interactive industrial report information result;
correcting the result description content of a preset result interaction strategy according to the result description content of each interactive industrial report information result, and transmitting the report description basic information set to the corrected result interaction strategy to obtain a corresponding interactive result description basic information set;
and correcting the result description content of the basic unit training thread according to the result description basic information set of each interactive industrial report information result and the corresponding basic information set described by the interactive result to obtain the report characteristic description thread.
7. The artificial intelligence based data processing method according to claim 6, wherein the step of modifying the result description content of the basic unit training thread according to the result description basic information set of each interactive industrial report information result and the corresponding basic information set of the interactive result description comprises:
calculating a model evaluation information characteristic vector between a result description basic information set of each interactive industrial report information result and a corresponding interactive result description basic information set;
and after updating the result description content of the basic unit training thread according to the model evaluation information feature vector, performing iterative configuration, and outputting a report form feature description thread obtained by configuration until the basic unit training thread meets the configuration ending condition.
8. The artificial intelligence based data processing method of claim 7, wherein the configuration end condition comprises at least one of:
the model evaluation information characteristic vector is not weakened in error any more;
the model evaluation information characteristic vector is lower than a set standard attenuation period;
the iterative configuration frequency reaches the set frequency.
9. An artificial intelligence based data processing system comprising a processor and a memory in communication with each other, the processor being configured to read a computer program from the memory and execute it to perform the method of any of claims 1 to 8.
10. A cloud platform, comprising:
a memory for storing a computer program;
a processor coupled to the memory for executing the computer program stored by the memory to implement the method of any of claims 1-8.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115563153A (en) * | 2022-09-23 | 2023-01-03 | 温仲恺 | Task batch processing method and system based on artificial intelligence and server |
| CN117176840A (en) * | 2023-11-02 | 2023-12-05 | 成都汉度科技有限公司 | Communication protocol identification method and system |
| CN117613925A (en) * | 2023-11-29 | 2024-02-27 | 重庆酷泓精典科技有限公司 | Intelligent control method and system for equipment with abnormal voltage |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115563153A (en) * | 2022-09-23 | 2023-01-03 | 温仲恺 | Task batch processing method and system based on artificial intelligence and server |
| CN115563153B (en) * | 2022-09-23 | 2023-11-24 | 湖南新艺信息技术有限公司 | Task batch processing method, system and server based on artificial intelligence |
| CN117176840A (en) * | 2023-11-02 | 2023-12-05 | 成都汉度科技有限公司 | Communication protocol identification method and system |
| CN117176840B (en) * | 2023-11-02 | 2024-03-12 | 成都汉度科技有限公司 | Communication protocol identification method and system |
| CN117613925A (en) * | 2023-11-29 | 2024-02-27 | 重庆酷泓精典科技有限公司 | Intelligent control method and system for equipment with abnormal voltage |
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